{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Timespan Demos\n",
    "\n",
    "Work in progress..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from music21 import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "luca = corpus.parse('luca/gloria').measures(1, 8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "tsCol = luca.asTimespans()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<TimespanTree {189} (0.0 to 24.0) <music21.stream.Score 0x11a261208>>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tsCol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<music21.tree.verticality.Verticality 0.0 {F3 F4 C5}>\n",
      "<music21.tree.verticality.Verticality 3.0 {F3 F4 D5}>\n",
      "<music21.tree.verticality.Verticality 3.5 {F3 C4 C5}>\n",
      "<music21.tree.verticality.Verticality 4.5 {F3 C4 A4}>\n",
      "<music21.tree.verticality.Verticality 5.0 {F3 C4 F4}>\n",
      "<music21.tree.verticality.Verticality 5.5 {F3 A3 F4}>\n",
      "<music21.tree.verticality.Verticality 6.0 {F3 F4}>\n",
      "<music21.tree.verticality.Verticality 6.5 {F3 F4 A4}>\n",
      "<music21.tree.verticality.Verticality 7.5 {F3 F4 C5}>\n",
      "<music21.tree.verticality.Verticality 8.5 {F3 F4 C5}>\n",
      "<music21.tree.verticality.Verticality 9.0 {C4 E4 G4}>\n",
      "<music21.tree.verticality.Verticality 10.5 {D4 F4 A4}>\n",
      "<music21.tree.verticality.Verticality 12.0 {C4 E4 G4}>\n",
      "<music21.tree.verticality.Verticality 15.0 {G3 G4 D5}>\n",
      "<music21.tree.verticality.Verticality 16.5 {A3 E4 C5}>\n",
      "<music21.tree.verticality.Verticality 17.5 {A3 E4 B4}>\n",
      "<music21.tree.verticality.Verticality 18.0 {D4 F4 A4}>\n",
      "<music21.tree.verticality.Verticality 18.5 {D4 F4 G4}>\n",
      "<music21.tree.verticality.Verticality 19.0 {D4 F4}>\n",
      "<music21.tree.verticality.Verticality 19.5 {C4 E4 G4}>\n",
      "<music21.tree.verticality.Verticality 20.0 {C4 F4 G4}>\n",
      "<music21.tree.verticality.Verticality 20.5 {C4 D4 G4}>\n",
      "<music21.tree.verticality.Verticality 21.0 {C4 E4}>\n",
      "<music21.tree.verticality.Verticality 21.5 {A3 E4}>\n",
      "<music21.tree.verticality.Verticality 22.0 {A3 C4 F4}>\n",
      "<music21.tree.verticality.Verticality 22.5 {B-3 D4 F4}>\n",
      "<music21.tree.verticality.Verticality 23.0 {G3 B-3 D4}>\n",
      "<music21.tree.verticality.Verticality 23.5 {B-3 D4 F4}>\n"
     ]
    }
   ],
   "source": [
    "for v in tsCol.iterateVerticalities():\n",
    "    print(v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "v4 = list(tsCol.iterateVerticalities())[4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<music21.tree.verticality.Verticality 5.0 {F3 C4 F4}>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{<music21.pitch.Pitch F3>, <music21.pitch.Pitch C4>, <music21.pitch.Pitch F4>}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v4.pitchSet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "f = sorted(v4.pitchSet)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<music21.pitch.Pitch F3>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<PitchedTimespan (5.0 to 6.0) <music21.note.Note F>>,)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v4.startTimespans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<PitchedTimespan (4.5 to 5.0) <music21.note.Note A>>,)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v4.stopTimespans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<PitchedTimespan (3.0 to 6.0) <music21.note.Note F>>,\n",
       " <PitchedTimespan (4.5 to 5.5) <music21.note.Note C>>)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v4.overlapTimespans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "v35 = tsCol.getVerticalityAt(3.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<music21.tree.verticality.Verticality 3.5 {F3 C4 C5}>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v35"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<PitchedTimespan (3.5 to 4.5) <music21.note.Note C>>,\n",
       " <PitchedTimespan (3.5 to 4.5) <music21.note.Note C>>)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v35.startTimespans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<PitchedTimespan (3.0 to 3.5) <music21.note.Note D>>,\n",
       " <PitchedTimespan (3.0 to 3.5) <music21.note.Note F>>)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v35.stopTimespans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<PitchedTimespan (3.0 to 6.0) <music21.note.Note F>>,)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v35.overlapTimespans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "elTsC = v35.startTimespans[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<PitchedTimespan (3.5 to 4.5) <music21.note.Note C>>, <music21.note.Note C>)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "elTsC, elTsC.element"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test previousVerticality with Rest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "v22 = tsCol.getVerticalityAt(22.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<music21.tree.verticality.Verticality 22.0 {A3 C4 F4}>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v22"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<PitchedTimespan (22.0 to 22.5) <music21.note.Note C>>,\n",
       " <PitchedTimespan (22.0 to 23.0) <music21.note.Note F>>)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v22.startTimespans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<PitchedTimespan (22.0 to 23.0) <music21.note.Note F>>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "elTSfollowingRest = v22.startTimespans[1]\n",
    "elTSfollowingRest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<PitchedTimespan (21.0 to 22.0) <music21.note.Note E>>,\n",
       " <ElementTimespan (21.5 to 22.0) <music21.note.Rest rest>>)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v22.stopTimespans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<music21.stream.Part Cantus>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "elTSfollowingRest.part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 115,
       "width": 748
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "score = tree.makeExampleScore()\n",
    "score.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "tsColSmall = score.asTimespans()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "tags": [
     "nbval-raises-exception"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<music21.tree.verticality.Verticality 0.0 {C3 C#3}>\n"
     ]
    },
    {
     "ename": "TimespanTreeException",
     "evalue": "PitchedTimespan <ElementTimespan (0.0 to 0.0) <music21.clef.BassClef>>, must be an PitchedTimespan",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTimespanTreeException\u001b[0m                     Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-30-4244ee6be833>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m         \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m         \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetAllVoiceLeadingQuartets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/git/music21base/music21/tree/verticality.py\u001b[0m in \u001b[0;36mgetAllVoiceLeadingQuartets\u001b[0;34m(self, includeRests, includeOblique, includeNoMotion, returnObjects, partPairNumbers)\u001b[0m\n\u001b[1;32m    901\u001b[0m         \u001b[0;32mfrom\u001b[0m \u001b[0mmusic21\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvoiceLeading\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mVoiceLeadingQuartet\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    902\u001b[0m         pairedMotionList = self.getPairedMotion(includeRests=includeRests,\n\u001b[0;32m--> 903\u001b[0;31m                                                 includeOblique=includeOblique)\n\u001b[0m\u001b[1;32m    904\u001b[0m         \u001b[0mallQuartets\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mitertools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcombinations\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpairedMotionList\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    905\u001b[0m         \u001b[0mfilteredList\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/git/music21base/music21/tree/verticality.py\u001b[0m in \u001b[0;36mgetPairedMotion\u001b[0;34m(self, includeRests, includeOblique)\u001b[0m\n\u001b[1;32m    996\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mstartingTs\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mstartTss\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    997\u001b[0m             previousTs = self.timespanTree.findPreviousPitchedTimespanInSameStreamByClass(\n\u001b[0;32m--> 998\u001b[0;31m                 startingTs)\n\u001b[0m\u001b[1;32m    999\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mpreviousTs\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1000\u001b[0m                 \u001b[0;32mcontinue\u001b[0m  \u001b[0;31m# first not in piece in this part...\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/git/music21base/music21/tree/timespanTree.py\u001b[0m in \u001b[0;36mfindPreviousPitchedTimespanInSameStreamByClass\u001b[0;34m(self, pitchedTimespan, classList)\u001b[0m\n\u001b[1;32m    302\u001b[0m             message = 'PitchedTimespan {!r}, must be an PitchedTimespan'.format(\n\u001b[1;32m    303\u001b[0m                 pitchedTimespan)\n\u001b[0;32m--> 304\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mTimespanTreeException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmessage\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    305\u001b[0m         \u001b[0mverticality\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetVerticalityAt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpitchedTimespan\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moffset\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    306\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0mverticality\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTimespanTreeException\u001b[0m: PitchedTimespan <ElementTimespan (0.0 to 0.0) <music21.clef.BassClef>>, must be an PitchedTimespan"
     ]
    }
   ],
   "source": [
    "for v in tsColSmall.iterateVerticalities():\n",
    "    if v:\n",
    "        print(v)\n",
    "        print(v.getAllVoiceLeadingQuartets())\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "lucaAll = corpus.parse('luca/gloria')\n",
    "tsCol = lucaAll.asTimespans()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "tags": [
     "nbval-raises-exception"
    ]
   },
   "outputs": [
    {
     "ename": "TimespanTreeException",
     "evalue": "PitchedTimespan <ElementTimespan (0.0 to 0.0) <music21.text.TextBox '1'>>, must be an PitchedTimespan",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTimespanTreeException\u001b[0m                     Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-32-ab857b8a0fd8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtsCol\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miterateVerticalities\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m     \u001b[0mvlqs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetAllVoiceLeadingQuartets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/git/music21base/music21/tree/verticality.py\u001b[0m in \u001b[0;36mgetAllVoiceLeadingQuartets\u001b[0;34m(self, includeRests, includeOblique, includeNoMotion, returnObjects, partPairNumbers)\u001b[0m\n\u001b[1;32m    901\u001b[0m         \u001b[0;32mfrom\u001b[0m \u001b[0mmusic21\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvoiceLeading\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mVoiceLeadingQuartet\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    902\u001b[0m         pairedMotionList = self.getPairedMotion(includeRests=includeRests,\n\u001b[0;32m--> 903\u001b[0;31m                                                 includeOblique=includeOblique)\n\u001b[0m\u001b[1;32m    904\u001b[0m         \u001b[0mallQuartets\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mitertools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcombinations\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpairedMotionList\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    905\u001b[0m         \u001b[0mfilteredList\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/git/music21base/music21/tree/verticality.py\u001b[0m in \u001b[0;36mgetPairedMotion\u001b[0;34m(self, includeRests, includeOblique)\u001b[0m\n\u001b[1;32m    996\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mstartingTs\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mstartTss\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    997\u001b[0m             previousTs = self.timespanTree.findPreviousPitchedTimespanInSameStreamByClass(\n\u001b[0;32m--> 998\u001b[0;31m                 startingTs)\n\u001b[0m\u001b[1;32m    999\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mpreviousTs\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1000\u001b[0m                 \u001b[0;32mcontinue\u001b[0m  \u001b[0;31m# first not in piece in this part...\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/git/music21base/music21/tree/timespanTree.py\u001b[0m in \u001b[0;36mfindPreviousPitchedTimespanInSameStreamByClass\u001b[0;34m(self, pitchedTimespan, classList)\u001b[0m\n\u001b[1;32m    302\u001b[0m             message = 'PitchedTimespan {!r}, must be an PitchedTimespan'.format(\n\u001b[1;32m    303\u001b[0m                 pitchedTimespan)\n\u001b[0;32m--> 304\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mTimespanTreeException\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmessage\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    305\u001b[0m         \u001b[0mverticality\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetVerticalityAt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpitchedTimespan\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moffset\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    306\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0mverticality\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTimespanTreeException\u001b[0m: PitchedTimespan <ElementTimespan (0.0 to 0.0) <music21.text.TextBox '1'>>, must be an PitchedTimespan"
     ]
    }
   ],
   "source": [
    "for v in tsCol.iterateVerticalities():\n",
    "    vlqs = v.getAllVoiceLeadingQuartets()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "bach = corpus.parse('bwv66.6')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "meterCol = lucaAll.parts[0].asTimespans(classList=(meter.TimeSignature,))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<TimespanTree {4} (0.0 to 275.0) <music21.stream.Part Cantus>>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meterCol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<TimespanTree {4} (0.0 to 275.0) <music21.stream.Part Cantus>>\n",
      "\t<ElementTimespan (0.0 to 0.0) <music21.meter.TimeSignature 6/8>>\n",
      "\t<ElementTimespan (81.0 to 81.0) <music21.meter.TimeSignature 2/4>>\n",
      "\t<ElementTimespan (185.0 to 185.0) <music21.meter.TimeSignature 6/8>>\n",
      "\t<ElementTimespan (275.0 to 275.0) <music21.meter.TimeSignature 3/4>>\n"
     ]
    }
   ],
   "source": [
    "print(meterCol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 160,
       "width": 748
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "c = corpus.parse('7thRegimentReel')\n",
    "c.measures(0, 3).show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠩⠩⠩⠼⠃⠲⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀\n",
      "⠼⠚⠀⠐⠊⠮⠉⠽⠯⠐⠊⠙⠋⠀⠮⠨⠽⠯⠮⠙⠾⠉⠮⠀⠿⠊⠋⠊⠨⠽⠋⠊⠛\n",
      "⠀⠀⠨⠯⠙⠚⠊⠿⠊⠋⠙⠀⠊⠐⠮⠉⠽⠯⠐⠊⠙⠋⠀⠮⠨⠽⠯⠮⠙⠾⠉⠮\n",
      "⠀⠀⠨⠿⠊⠋⠊⠨⠽⠋⠛⠋\n"
     ]
    }
   ],
   "source": [
    "c.measures(0, 6).show('braille')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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